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Jurnal Mantik
Published by Institute of Computer Science
ISSN : -     EISSN : 26854236     DOI : -
Core Subject : Economy, Science, Education,
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media
Jurnal Mantik (Manajemen, Teknologi Informatika dan Komunikasi) is a scientific journal in information systems/informati containing the scientific literature on studies of pure and applied research in information systems/information technology,Comptuer Science and management science and public review of the development of theory, method and applied sciences related to the subject. Jurnal Mantik Penusa is published by Institute of Computer Science (IOCS). Editors invite researchers, practitioners, and students to write scientific developments in fields related to information systems/information technology,Comptuer Science and management science). Jurnal Mantik is issued 4 (FOUR) times a year.
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Articles 2,151 Documents
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Analysis of Spirit and Job Satisfaction on the Performance of Employees of PT. Dodorindo Jaya Abadi Tanjung Morawa Etin Indrayani; Robin Robin
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

This study aims to determine whether there is an influence of spirit and work satisfaction on the work performance of employees. The population in this study were all employees who worked at PT. Dodorindo Jaya Abadi Tanjung Morawa as many as 447 employees. The sampling technique used was the Slovin technique with a significance of 10% with a sample of 82 employees. In this study, a questionnaire will be distributed which is measured by a Likert scale. Data analysis used multiple linear regression analysis. The results showed that there was an effect both partially and simultaneously where the spirit variable partially had a tcount (4.694) greater than ttable (1.990) with a significant (0.00) less than 0.05, while the work satisfaction variable had a tcount value (5.950) is higher than ttable (1.990) with a significant (0.00) smaller than 0.05. Simultaneously, the variables of spirit and work satisfaction have a value of Ftable (3.11) and a significance = 5% (0.05), namely Fcount (25.338) and sig.a (0.000a). This shows that the results of the study accept Ha and reject H0, while the coefficient of determination R Square is 0.391. This shows that the variables of spirit and work satisfaction explain their influence on the work performance by 39,1%. While the remaining 60,9% is the influence of other independent variables not examined in this study.
Impact Of Leadership Style On Job Satisfaction Of Administrative Staff Of Budidarma University Medan Ikwan Lubis; AMH. Sihite; Edizal Hatmi; Ilhamsyah Ilhamsyah
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The purpose of this study was to find out the Impact of Superior Leadership on job satisfaction of Administrative Staff at BUDI DARMA University, Medan and to analyze whether superior Leadership variables affect Employee Employee Satisfaction Administration (Case Study: BUDIDARMA University Medan), The Data Collection Method used in this study is to use questionnaires, The data analysis model used is simple Linear Regression analysis. Sampling uses the stratified random sampling method, which first classifies a population, Probability sampling, which is a sampling technique that provides equal opportunities for each element (member) of the population at once the sample.The results of research at BUDIDARMA University, in Medan showed that superior leadership variables have an impact on satisfaction that can affect administrative staff to improve their work, this shows that the level of job satisfaction of administrative staff has not been considered maximally by the management of the company.
Implementation of Random Forest for Motif Classification Based on Sift Ahkyar Khadafi; Muhammad Iqbal
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Songket an example of intangible cultural heritage found in Indonesia. Songket, especially Songket Palembang, has a lot of variety depending on the features of each place. When compared to Songket from other locations, Palembang Songket has more features. Songket Palembang has a high motive, quality, and complexity in the manufacturing process, in addition to its historical significance. Using Scale-Invariant Feature Transform (SIFT) feature extraction, the Random Forest approach was employed to identify the Songket Palembang motif image in this study. The SIFT approach involves the steps of extrema detection scale space, keypoint localization, orientation assignment, and keypoint descriptor in the feature creation process. The Random Forest categorization uses the resulting feature. In this study, 115 photographs of each sort of Songket theme were used, including Chinese Flowers, Beautiful Flowers, and Pulir. Each Songket Palembang motif's five colors were used to create the image. For each Songket Palembang motif, 100 and 15 training and test data were used, respectively. The test results show that the SIFT and Random Forest methods for the classification of Songket Palembang motifs can provide fairly good accuracy, with overall accuracy of 92.98 percent, per class accuracy of 94.07 percent, precision 92.98 percent, and recall 89.74 percent for the SIFT and Random Forest methods, respectively.
Effect of Leadership Style on Employee Performance at PT. Hevea Indonesia Works with Work Discipline as the Intervening Variable Jopinus Ramli Saragih; Jumadiah Wardati
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

This research shows. (1) It can be seen that the magnitude of the adjusted R square value is 0.175 or 17.5%. This shows that Work Discipline (Z) and Leadership Style (X) can explain Employee Performance (Y) by 17.5%, the remaining 82.5% (100% - 17.5%) is explained by other variables outside the model. this research. (2) The results of the t-test (partial) can be seen that the obtained tcount (4,363) > ttable (2,048), as well as the significance value of 0.00 <0.05, it can be concluded that the first hypothesis is accepted, meaning that the Leadership Style variable (X) positive and significant effect on Work Discipline (Z). (3) The results of the t-test (partial) can be seen that the value of tcount (1.917) ttable (2.048), and the significance value of 0.367 0.05, it can be concluded that the second hypothesis is rejected, meaning that Leadership Style (X) has a significant effect on employee performance. (Y). (4) The results of the path analysis test show that the direct effect of variable X on variable Y is 0.200. Meanwhile, the indirect effect through the Z variable is 0.636 x 0.329 = 0.2092. From the calculation results obtained, the indirect effect through the Z variable is greater than the direct effect on the Y variable
Decision Tree Algorithm and Gini Calculation for Puppies Skin Disease Diagnosis Khairun Annisa; Arpan Arpan
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

To put it another way, an expert system is a computer system that can store and reproduce knowledge in order to solve a problem. It is also possible to employ expert systems to assist a specific field with problem-solving, and the expert system serves to keep the necessary parties working together. Software or computer programs that provide guidance and assistance in specialized subjects, such as science, engineering, mathematics, medicine, and education can be referred to as expert systems. The expert system can be used to perform diagnostics on pets. This article aims to discuss the implementation and study of an expert system that assists users in determining the ailment that pets, particularly dogs, are suffering from. The system can generate a symptom diagnostic of a skin illness using a decision-tree algorithm. Veterinarians provided data sets on a variety of disorders. There were 105 cases of 11 diseases and 11 symptoms in the dataset used in this study. The scikit-learn library was also used to train decision trees. Following the creation of a decision tree, a case study analysis was conducted using ten real-world examples provided by the veterinarian. Participants who own dogs received questionnaires in addition to those used for analysis. In the study, 25.8% of respondents said they strongly agreed with the expert system, and 32.3% said they agreed that the expert system helped explain the ailment their dog had. A further 80 percent of the instances provided by vets can be accurately determined by the system. When four independent tests were run, the mean system prediction was found to be 67.6 percent.
Decision Tree Model for Predicting Work Schedules Using Scikit-Learn Siti Hapsoh Lubis; Muhammad Iqbal
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Predicting category and numerical data, such as working schedule data, is difficult since it necessitates a specific process. A decision tree is one of many categorization methods that can handle both category and numerical input. Scikit learn, a python library that may be used for decision trees, is one example. Although Scikit-optimized learn's CART algorithm could only handle numerical data, it did provide certain features to deal with categorical data. To forecast working schedules, this study used scikit-learn to create a decision tree model. There are 54 variables, three of which are category and one of which is numerical. A 6-depth decision tree model was created as a result of the implementation. The evaluation yielded a positive outcome, with accuracy and precision above 0.7 and 0.9, respectively. The optimal division of data is 30% validation and 70% training. In comparison to KNN, the decision tree model has higher accuracy, with decision tree accuracy exceeding 0.8 while KNN accuracy is below.
Using the Matlab App to Detect Objects by Color with HSV Color Segmentation Rindi Antika; Muhammad Iqbal
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Object detection using computer vision algorithms is a crucial procedure for accurately detecting items in a three-dimensional image. When using the color segmentation method with HSV color, an image segment object in the shape of a blob is created, which the computer can detect. The color sample will provide a value that will be the reference for the filter range in the segmentation process based on the test findings. During the process, the number of objects identified according to the given color will be determined.
Application of Data Mining to Predict Work Accident Rates using Rapid Miner Sapna Indah Br Ginting; Muhammad Iqbal
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Working safety is strongly linked to machines, aircraft, and work tools in the workplace runway and its surroundings, as well as how to work. The corporation must provide this protection since it is a human right. According to ILO (International Labor Organization) estimates, 2 million people die each year as a result of work-related issues around the world. A total of 354,000 persons died as a result of these accidents. The rate of fatal accidents in underdeveloped countries is four times that in developed countries. The agriculture, construction, mining, forestry, and fisheries industries all have hazardous jobs that account for the majority of accidents. This research is descriptive in nature, examining work accidents that occur based on secondary data and making predictions to estimate the amount of work accidents using a Data Mining approach utilizing Rapid Miner to determine the level of work accidents. Rapid miner is a data mining processing software that includes tools for creating decision trees and a data mining engine that may be used in its own products. The data utilized was collected from the Industrial Safety and Health Analytics Database as secondary data. The database's content consists primarily of accident records from 12 distinct factories in three different nations, with each row representing a 439-data-row accident incident. According to the findings, 11 of the 12 factories have an accident rate of level I; the third factory (level 03) has an accident rate of level IV on the Risco Critico power lock; and factory 11 (local 11) does not have a crash lift.
Comparison Analysis of SVM Algorithm with Linear Regression in Predicting used Car Prices Yennimar Yennimar; Kelvin Kelvin; Suwandi Suwandi; Amir Amir
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

During the high activity , car has become a basic need. On the other hand, the price of new car is getting higher. To meet these needs, people are looking for alternatives by buying used cars. One of the factors to consider when looking for a used car is price. In this study, two algorithms that are quite popular in terms of prediction will be tested, namely the Support Vector Machine algorithm and the Linear Regression algorithm in predicting used car prices. Support Vector Machine is a supervised learning method that analyzes data and recognizes patterns for regression. Support Vector Machine has the ability to solve linear and nonlinear problems. Linear Regression Algorithm is a modeling and analysis of numerical data consisting of one or more independent variables and the value of the dependent variable, with the aim of using regression analysis to estimate the value of the dependent variable based on the value of the independent variable. The result of this research is that the SVM method can perform better than linear regression. SVM can perform kernel-tricks that can handle non-linear data, thus making the non-linear data appear to be linear. but this cannot be done by Linear regression.
The Effect of the Use of Collaborative Educational Supervision on Increasing Lecturer Performance in Online Learning Ari Lestari
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Based on article 20 of the Law on Teachers and Lecturers, it is explained that in carrying out professional duties, there are several obligations that must be fulfilled, namely planning, implementing and assessing and evaluating learning, improving and developing qualifications and competencies, having objective actions, upholding the rules that have been outlined and maintaining and foster a sense of national unity and integrity. One of the indicators of success in improving the quality of education is that the learning process is not just about imparting knowledge, but is more focused on internalizing the development of cognitive, affective and psychomotor aspects as well as bathing. Then the collaborative education supervision is carried out periodically and gradually which will result in an improvement in learning which can be achieved by measuring the value obtained by students in one unit such as a semester or department. In general, the use of collaborative supervision has an influence on performance by looking for forms or methods or learning strategies that are in accordance with the majors taken by students.

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